Estimating Tumor Growth Rates In Vivo

Overview

Journal Bull Math Biol

Publisher Springer

Specialties Biology
Public Health

Date 2015 Oct 21

PMID 26481497

Citations 40

Authors

Anne Talkington

Rick Durrett

Affiliations

Soon will be listed here.

Abstract

In this paper, we develop methods for inferring tumor growth rates from the observation of tumor volumes at two time points. We fit power law, exponential, Gompertz, and Spratt’s generalized logistic model to five data sets. Though the data sets are small and there are biases due to the way the samples were ascertained, there is a clear sign of exponential growth for the breast and liver cancers, and a 2/3’s power law (surface growth) for the two neurological cancers.

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